DBMS > CrateDB vs. etcd vs. Oracle NoSQL vs. SAP HANA

System Properties Comparison CrateDB vs. etcd vs. Oracle NoSQL vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Distributed Date Store based on Lucene

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS
Search engine

Key-value store

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.97
Rank	#178	Overall
	#86	Relational DBMS
	#13	Search engines

Score	10.88
Rank	#47	Overall
	#5	Key-value stores

Score	4.74
Rank	#82	Overall
	#15	Document stores
	#13	Key-value stores
	#44	Relational DBMS

Score	55.09
Rank	#21	Overall
	#13	Relational DBMS

Website

crate.io

etcd.io
github.com/etcd-io/etcd

www.oracle.com/database/technologies/related/nosql.html

www.sap.com/products/hana.html

Technical documentation

crate.io/docs

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.oracle.com/en/database/other-databases/nosql-database/index.html

help.sap.com/hana

Developer

Crate

Oracle

SAP

Initial release

2013

2011

2010

Current release

3.4, August 2019

22.1, May 2022

2.0 SPS05 (June 26, 2020), June 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

All OS with a Java 7 (and higher) VM

FreeBSD
Linux
Windows

experimental

Linux
Solaris SPARC/x86

Appliance or cloud-service

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints

SQL-like DML and DDL statements

yes

APIs and other access methods

ADO.NET

community maintained client
JDBC
MQTT (Message Queue Telemetry Transport)
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

gRPC
JSON over HTTP

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
Ruby

community maintained client
Scala

community maintained client

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

SQLScript, R

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read Your Own Writes Consistency

for primary key lookups

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

unique row identifiers can be used for implementing an optimistic concurrency control strategy

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

yes

User concepts

Access control

rights management via user accounts

Access rights for users and roles

yes

More information provided by the system vendor

Specific characteristics

CrateDB is an open source distributed SQL database that spreads data and processing...
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Competitive advantages

CrateDB is typically used in operational analytics applications, particularly those...
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Typical application scenarios

CrateDB is ideal for integrating and analyzing streams of data--often machine-generated--in...
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Key customers

CrateDB customers include McAfee, Qualtrics , Nokia, NBC Golfnow , Digital Domain...
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Market metrics

The CrateDB open source project was started in 2014. CrateDB was the winner of TechCrunch...
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Licensing and pricing models

CrateDB pricing CrateDB Community Edition is open source and free to use under the...
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